Evidence map›Paper›PMID 42233653›Full record

ArticleJournal of neuromuscular diseases2026

MDBiomarkers: A queryable biomarkers database integrating multiple serum and tissue datasets for Duchenne muscular dystrophy.

Wangshu Tu, Rebecca A Tobin, Leenah Abdelrazeq, Kaitey Guite, Cristina Al-Khalili Szigyarto, Roula Tsonaka, Chiara Degan, Yuri E M van der Burgt, Jordi Díaz-Manera, Michela Guglieri and 3 more

Abstract read
In one paragraph

Article in Journal of neuromuscular diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Wangshu TuDepartment of Health Sciences, Carleton University, Ottawa, Ontario, Canada.
Rebecca A TobinDepartment of Health Sciences, Carleton University, Ottawa, Ontario, Canada.
Leenah AbdelrazeqDepartment of Health Sciences, Carleton University, Ottawa, Ontario, Canada.
Kaitey GuiteDepartment of Health Sciences, Carleton University, Ottawa, Ontario, Canada.ORCID 0009-0002-1251-786X
Cristina Al-Khalili SzigyartoDepartment of Protein Science, KTH The Royal Institute of Technology, Stockholm, Sweden.
Roula TsonakaLeiden University Medical Center, Leiden, Netherlands.
Chiara DeganLeiden University Medical Center, Leiden, Netherlands.
Yuri E M van der BurgtLeiden University Medical Center, Leiden, Netherlands.ORCID 0000-0003-0556-5564
Jordi Díaz-ManeraJohn Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle, UK.
Michela GuglieriJohn Walton Muscular Dystrophy Research Centre, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle, UK.
Pietro SpitaliLeiden University Medical Center, Leiden, Netherlands.
Yetrib HathoutSchool of Pharmacy and Pharmaceutical Sciences, Binghamton University, New York, USA.
Utkarsh J DangDepartment of Health Sciences, Carleton University, Ottawa, Ontario, Canada.ORCID 0000-0003-4120-2015

Funding

Biomarker Signatures for Duchenne Muscular DystrophyR61NS119639 · NINDS · STATE UNIVERSITY OF NY,BINGHAMTON · PI DANG, UTKARSH J, HATHOUT, YETRIB · 2022 to 2024
$1.6M
NINDS NIH HHS R61 NS119639
6 · The paper itself

Abstract

BackgroundFit-for-purpose biomarkers are urgently needed in Duchenne muscular dystrophy (DMD). However, biomarker efforts in DMD have traditionally been hampered by a lack of reproducibility due to small sample sizes, confounders such as treatment and age, and discordant findings from different technologies. Moreover, there is no central resource to get an overview of cumulative published evidence. Hence, many researchers often start with new discovery studies, which are time-consuming and costly.ObjectiveBuild a dynamic, searchable, and easy-to-use biomarker platform for DMD.MethodsThousands of molecular (serum proteins and muscle mRNA) markers from multiple studies (28 analyses) were compiled. Findings were obtained from supplemental material of published manuscripts or by following standardized pipelines on available raw data. These findings were annotated with important attributes (e.g., age range, treatment, etc.). Evidence was aggregated around each biomarker's association with DMD, treatment, age, clinical outcomes, as well as other markers.ResultsThe interactive Shiny application on https://www.mdbiomarkers.com provides exportable summaries of serum protein and muscle tissue mRNA findings. This also permits new knowledge to be generated for nuanced meta-analyses, rather than being restricted by a single study's finding and p-value. A tutorial is provided on the website. This resource is planned to be continually updated with new/additional findings to fulfill the aim of a living biomarker resource.ConclusionsThe resource developed will reduce preparatory time to distill evidence around important biomarker candidates providing summary estimates around individual studies' effect sizes, help assess cumulative evidence, and help with experimental design of future experiments.

Indexed as

biomarker associationsbiomarker websiteDMD biomarker databaseDuchenne muscular dystrophymRNAproteomicsreproducibilityserumShiny applicationtissue

Identifiers

PMID42233653
PMCPMC13437981

What Socratic holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.